code: def _unstack_pytree(xs):
      flat_xs, inspec = pytree.tree_flatten(xs)
      if not all(isinstance(xs, torch.Tensor) for xs in flat_xs):
          raise RuntimeError(f"Leaves of xs must be Tensor {flat_xs}")
  
      if not all(xs.shape[0] == flat_xs[0].shape[0] for xs in flat_xs):
          raise RuntimeError(
              f"Leaves of xs must have same leading dimension size {[xs.shape for xs in flat_xs]}"
          )
  
      ctx = (
          FunctionalTensorMode
          if any(isinstance(x, FunctionalTensor) for x in flat_xs)
          else nullcontext
      )
      with ctx():
          a = zip(*flat_xs)
  
      pytrees = []
      for tuple in a:
          pytrees.append(pytree.tree_unflatten(tuple, inspec))
      return pytrees
  
imports: from contextlib import nullcontext
  import torch
  import torch.utils._pytree
  from torch._C import DispatchKey
  from torch._dispatch.python import suspend_functionalization
  from torch._functorch.aot_autograd import AOTConfig, create_joint, from_fun
  from torch._higher_order_ops.cond import _has_potential_branch_input_alias, _has_potential_branch_input_mutation, UnsupportedAliasMutationException
  from torch._ops import HigherOrderOperator
  from torch._subclasses.fake_tensor import FakeTensorMode
  from torch._subclasses.functional_tensor import FunctionalTensor, FunctionalTensorMode, unset_functional_temporarily
  from torch.fx.experimental.proxy_tensor import disable_proxy_modes_tracing, make_fx, ProxyTorchDispatchMode, track_tensor_tree
  from torch.multiprocessing.reductions import StorageWeakRef
label_desc: Use image node_id 4 for calling a global function with example usage: _unstack_pytree(xs) and returns: pytrees